BackgroundRecently, pattern recognition methods have been deployed in the classification of multiple activation states from mechanomyogram (MMG) signals for the purpose of controlling switching interfaces. Given the propagative properties of MMG signals, it has been suggested that MMG classification should be robust to changes in sensor placement. Nonetheless, this purported robustness remains speculative to date. This study sought to quantify the change in classification accuracy, if any, when a classifier trained with MMG signals from the muscle belly, is subsequently tested with MMG signals from a nearby location.MethodsAn arrangement of 5 accelerometers was attached to the flexor carpi radialis muscle of 12 able-bodied participants; a reference accelerometer was located over the muscle belly, two peripheral accelerometers were positioned along the muscle's transverse axis and two more were aligned to the muscle's longitudinal axis. Participants performed three classes of muscle activity: wrist flexion, wrist extension and semi-pronation. A collection of time, frequency and time-frequency features were considered and reduced by genetic feature selection. The classifier, trained using features from the reference accelerometer, was tested with signals from the longitudinally and transversally displaced accelerometers.ResultsClassification degradation due to accelerometer displacement was significant for all participants, and showed no consistent trend with the direction of displacement. Further, the displaced accelerometer signals showed task-dependent de-correlations with respect to the reference accelerometer.ConclusionsThese results indicate that MMG signal features vary with spatial location and that accelerometer displacements of only 1-2 cm cause sufficient feature drift to significantly diminish classification accuracy. This finding emphasizes the importance of consistent sensor placement between MMG classifier training and deployment for accurate control of switching interfaces.

We calculated the properties of a graphene monolayer on the Ir(111) surface, using the model in which the periodicities of the two structures are assumed equal, instead of the observed slight mismatch which leads to a large superperiodic unit cell. We used the density functional theory approach supplemented with the recently developed van der Waals-density function (vdW-DF) non-local correlation functional. The latter is essential for treating the vdW interaction, which is crucial for the adsorption distances and energies of the rather weakly bound graphene. When additional iridium atoms are put on top of graphene, the electronic structure of C atoms acquires the sp3 character and strong bonds with the iridium atoms are formed. We discuss the validity of the approximations used and their relevance to other graphene–metal systems.

Aim: The prognostic value of circulating antibodies to oxidized low-density lipoprotein (anti-oxLDL) in patients with coronary heart disease is not completely clear. We aimed to investigate the association between levels of anti-oxLDL in three groups of patients with different grades of severity of coronary heart disease. Patients and methods: The study included 101 patients classified into three groups: one (N=35) with acute myocardial infarction (AMI), a group (N=35) with angiographicallly proven coronary artery disease (APCAD), and a group without angiographicallly proven coronary artery disease (N=31) designated as a control group. Levels of IgG anti-oxLDL antibodies were meausured by enzyme-linked immunosorbent assay. Results: Mean anti-oxLDL value was significantly higher in patients with AMI than in patients with APCAS (1342.1±581.5 mIU/ml vs. 553.0±183.3 mIU/ml, p<0.001), as well as compared with control group (1342.1±581.5 mIU/ml vs. 246.5±114.3, p<0.001). Similarly, significant difference in anti-oxLDL levels was found between the patients with APCAS and control group (p<0.001). Conclusions: The present study showed that elevated levels of anti-oxLDL are positively related with a severity of coronary artery disease. Hence, elevated levels of anti-oxLDL may identify patients with unstable coronary heart disease. Oxidized LDL in circulating plasma could serve as a marker of cardiovascular events.

SUMMARY: We present the central velocity dispersion measurements of the nearby galaxies from the Sloan Digital Sky Survey (SDSS). Using the sample from the paper by Ho et al. 2009, we have selected 23 galaxies for which we calculate the velocity dispersion. We have used the Penalized Pixel-Fitting code (Cappellari and Emsellem2004) to measure the velocity dispersion throughout the four chosen spectral regions: (3800,4568)” (4568,5336)” (5336,6104) and (6104,6872)” In all these regions, we have separately calculated dispersions and corresponding errors. We found that the measured values may vary with the change of spectral region, but, if weighted properly with the measure of the goodness of the flt, the flnal results will be shifted coloser to those for the best fltting regions. We have also tested how the use of difierent spectral libraries (Miles, Valdes and Elodie databases) in∞uences measurements and we showed that they do not afiect measurements much. However, Elodie stellar library introduces the smallest errors in the velocity dispersion and it is the most stable throughout all four spectral regions. For these reasons it should be used preferentially when dealing with the SDSS spectra. We compare the results with the above mentioned paper and flnd a reasonable agreement. The agreement with the dispersions available in the HyperLeda database is very poor. The best agreement is obtained with SDSS measurements. We believe that our measurements are useful since SDSS velocity dispersions measurements are not available for many galaxies and the method of calculation of the velocity dispersion outlined in this work enables calculation of velocity dispersion for any galaxy. Of course, spectra with signal-to-noise ratio below 20 should be taken with caution.